The Greatest “Tech-Onomic Push-Pull” in Human History

At the recent 50th Design Automation Conference (DAC) in Austin, Texas, Synopsys’ co-founder, chairman and co-CEO, Aart de Geus, gave a Visionary Talk on how the semiconductor industry is in the midst of one of the greatest “tech-onomic” exponentials in human evolution. In his talk, Aart outlined how human leaps historically have been made up of 50 years of “technology push” followed by 50 years of “applications pull” – i.e. the “push-pull of tech-onomics.” Read the complete text of Aart’s talk below for his perspective on how in this era of exponentials we will continue to accelerate innovation. You can also view the video — The Greatest “Tech-Onomic Push-Pull” in Human History.

Fifty Years of Design Automation!

Fifty years, and we, EDA, are enabling the greatest “Tech-Onomic Push-Pull” in human history.

If we could glimpse back to our age from the distance of even just a hundred years, we’d see that right now, we’re in the midst of one of the greatest techonomic exponentials of human evolution.

These human leaps are invariably made up of 50 years of “technology push,” followed by 50 years of “applications pull.” Let me unpack this idea of “techonomic push-pull” by looking at two major human leaps: the early Renaissance, and the Industrial Age.

In 1451, Johannes Gutenberg invented a machine using moveable typeset. Combined with new oil-based paint, (dare I say “litho?”) and a growing availability of rag paper, (dare I say “silicon?”), and... Voila! The printing press was born. Overnight, the availability of books exploded.

Compared to only a few pages by a hard-working monk, a single press could pump out 3,600 per day. That’s a fabulous increase!

In all fairness, both the Koreans and Chinese had experimented with wooden-bloc-based printing machines, but the large number and complexity of the letters made it considerably more difficult to get the same leverage. Be it as it may, by 1500 (around 50 years later) printing presses throughout Europe had already produced more than 20 million volumes: that’s an impressive 103 or so increase.

Of course, initially presses were dedicated to producing bibles, but it took only a very short time to print the first pamphlet incorporating a crude picture of the pope sitting on a toilet! This only shows how quickly techonomic exponentials shake up the establishment, and question the norms of thinking.

They also bring about pushback.

Just imagine the nobility of the time commenting: “Why do people need books since they can’t read?” Yes, why books if you can’t read?

It’s hard to foresee and appreciate exponential impacts. Wasn’t it IBM’s founder, Thomas J. Watson, who predicted there would be a world market for maybe only five computers? Or more fairly, whenever I comment on Facebook, my own daughters react, “Oh Daddy, you SO don’t get it...” Exponentials cannot be stopped, nor predicted by the establishment!

After the initial “Tech Push” invariably follows the “Onomic Pull,” in which emerging applications vastly leverage the impact of the initial invention. And this is exactly what happened.

In 1501 Aldus Manutius, a Venetian printer, started to print a new, more “mobile,” format of books. These were both cheaper and smaller, and easy for “gentlemen of leisure,” (like myself) to carry in their pockets.

Now, I don’t know if he called his new format a “Kindlelus,” but this “standardization” and “mobility” of information, insights, science, and entertainment opened the western European mind. It directly impacted human self-knowledge and understanding of the world.

The 50-year printing press “technology push” unleashed the next 50 years of economic “applications pull.” And with an estimated 200 million books produced in the 1500’s, clearly another “zero” had been added to our exponential!

An equally massive “push-pull” occurred in the industrial age around 1750. That’s between when Savrey’s patented of a 1 hp steam-engine, and Watt and Bouton formed an engine-building partnership of great impact.

Here too, the first fifty years were dedicated to crucial technical enablement, necessary enablement, as the original steam boilers had an unfortunate tendency to explode at inconvenient times.

However, by 1800, advances in metallurgy, piston tolerances, riveting, and so on had proceeded rapidly, and an estimated 10,000 hp was already supplied by steam. Just 15 years later, this figure had grown to over 200,000 hp, leading to a 106 exponential evolution in less than 100 years.

The technology push was greatly amplified by the pull of applications, ranging from water pumps, mills, and industrial factories, to the “mobile apps”—here’s that word again—“mobile” steam locomotives, steam ships, and later, self-propelled cars.

By now, you can probably see the similarities to our last and our next 50 years of high tech.

Of course, our exponentials are all called “Moores’ Law.” I always thought that this was a well-chosen name. After all, we’ve delivered more, and more, and more in quite unbelievable fashion. And even if Gordon misspells his name with a double “o,” his observation, which turned into a prediction, which turned into a law, which turned into milestones and schedules, which turned into never-ending EDA employment, was quite astute.

While we can pin-point the invention of the transistor to 1948, it is really the combination of Boolean algebra, digital transistor switches and storage, IC connectivity, and the symbiosis of hardware and software that characterizes the “tech” part of our journey.

The similarities to the printing press are really uncanny.

Our simplification of vocabulary into only ones and zeros, leveraged by over 50 years of utterly unexpected manufacturing and design prowess, made possible the universal standard of information, and its treatment.

Moreover, we use the most advanced computers to design the very chips that go into the most advanced computers, to design the very chips that go into... Well, it’s like that great Escher drawing showing two hands with a pencil in each, drawing the other in circular motion. That is the essence of a positive feedback loop. The pathway to machine learning is thus well lit, and well on its way.

And we, EDA, are central to enabling that future.

EDA has been intimate with every semiconductor iteration, every technical twist and turn, and every premature death announcement of Moore’s Law.

Oh sure, I recall users in the mid-nineties complaining about “the design gap” and EDA tools not being good enough. Okay, we may have had a few of our own exploding boilers. But today, our industry is absolutely on par with all the other disciplines needed for state-of-the-art 14 and 10-nm chips.

Not only have we mastered the exponential scale complexity growth, but we are optimizing multi-dimensional systemic complexity as well! The hit rates for high-end “first-time right” chips are unbelievably good!

So while we’re at it, let’s take some credit for the numbers, too!

Starting from one in 1948, a billion-transistor chip is absolutely feasible today. That’s 109 ! Take that, Renaissance!

And by the way, our “font size” is 10-9 meters. Gutenberg, I’d like to see you print that without smearing some ink!

And, we are not stopping yet! FinFETs, in my opinion, are a breakthrough. They not only change the performance/power ratio of the transistor, but one can see single-digit nanometer manufacturing on the horizon. New applications will absolutely gobble this up.

Now, I can hear some of you say: “Yeah, but manufacturing is becoming more expensive, and design is definitely becoming more difficult. Isn’t that gonna kill progress?”

Well, this is why the notion of techonomic push-pull is so important.

For starters, let’s agree that we’ve clearly entered the “onomics pull” phase of the digital age. Around 2000, computation and “mobility” massively converged. The internet-“standard” became the lingua franca of not only modern technology, but of human knowledge-accumulation and sharing, period.

This tsunami of computation and communication power has already unleashed fabulous new application exponentials.

It’s only a dozen years ago that the human DNA was completely sequenced. This created a map of life similar in impact to the first maps that finally showed the world as round.

We’re now on the verge of a complete human DNA sequence for less than $1,000. Meanwhile, innumerable studies are exploring not only genomic understanding, but are rapidly driving towards genetic therapy.

Be it in biology, health, transportation, energy, or big data, these fields are all experiencing their own follow-on exponential revolutions. Not only will everything be modeled, but gradually computational smarts will be introduced everywhere.

Indeed, these fields all follow the EDA playbook! If you can model, you may be able simulate. If you can simulate, you can analyze and verify. If you can analyze, you can optimize. And if you can optimize, you can ultimately synthesize and automate!

Following this trajectory, no modeling project has ever been more daunting and promising than the most complex computer ever: the human brain!

You may have read that the Obama administration has launched a national brain modeling initiative. But even before this, brain research had already seen tremendous progress!

For example, six months ago, probes were implanted in the brain of a paraplegic woman. These probes pick up brain waves, which are passed on to a computer interpreting the signals. The computer then drives a robotic hand with which the woman can pick up and eat a piece of chocolate.

This is possible today: thoughts... controlling sophisticated movement... to satisfy an ancient craving!

There’s no doubt that DNA modeling, brain modeling, and systematic utilization of sensors on and in the body will bring not only fundamental new understanding but also modification of who we are, and how we function.

The same will happen to the macro world. Sensors, modeling, and analysis will bring the insights needed to finally take action on global warming and the acidification of our oceans. I sure hope we’ll also find the right balance between the utter loss of privacy, and the most amazing shopping experience you can imagine!

Here is my point for our industry. When we make chips yet another 10X, or even 100X, higher performance and/or lower power, the potential new applications will be so ground-breaking that paying for the needed chips will only be a rounding error, compared to the value made possible.

For the last five years, semiconductors have been stuck at about $300B in revenue per year. EDA and IP are in the same boat, and a mere 2 percent of this! Compared to the revenue and valuations of systems and application-providers such as Apple, Google, Facebook, Baidu and others, our industry is peanuts.

Yet still, most people in our industry believe Moore’s law “dictates” that transistors at the next node have to always be cheaper, yet again.

Let me be the contrarian and propose to you that the “push to pull” transition is also the tipping point from strictly cost, to value and impact.

As we design true smarts into chip—as biology meets machine-based intelligence—the impact will be so big that revolutionary new applications will find the funding. Semiconductors and EDA are the enablers. Semiconductors and EDA economics will grow.

With another 10 to 100X, we’re in striking distance of putting machine intelligence—smarts—in ... well... everything! Granted, these chips will be challenging to manufacture, and they’re also really tough to design.

But we love tough! Our first and middle names stand for tough. EDA: Extremely Difficult Automation. Count us in, folks! We will deliver.

I was not personally part of the first generation of EDA, but I know well and have met many of the humble pioneers that built our industry. They are giants in my book.

I am part of the second generation, and know what it took to get to the most advanced state-of-the-art technology, and become the industry “behind the high tech curtain.”